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Summary: This article investigates the devise issue of a practical finite‐time output‐tracking control for uncertain nonlinear nonstrict‐feedback systems subject simultaneously to time‐varying output constraints (TVOC), actuator saturation, and bounded unmatched disturbances. An adaptive fuzzy approximator‐based control system is devised using the dynamic surface control (DSC) concept. System output constraints are addressed by employing an appropriate barrier Lyapunov function. Adaptive fuzzy disturbance observers are constructed to practically deal with time‐varying unmatched but bounded disturbances. It is verified via Lyapunov stability analysis and simulation experiments that all closed‐loop signals remain bounded, the output tracking error practically converges in finite time to a tiny but adjustable neighborhood around the origin, and the system output stays within its required time‐varying bounds. [ABSTRACT FROM AUTHOR]

Epstein-Barr Virus (EBV), or Kissing Virus, is a member of the Herpes virus that can be a contributory factor for compromised pregnant, high-risk aborted women worldwide. The present study aimed to detect high-risk EBV by the Monospot test for pregnant, high-risk aborted women, to detect immunoglobulin IgM and IgG for EBV using Enzyme-linked immunosorbent assay (ELISA) technique, to distinguish the infections as acute, chronic, or reactivated, and to determination of Enzymes as Aspartate Transaminase (AST), Alkaline phosphatase (ALP), and Alanine Transaminase (ALT).A cohort of 91 serum samples were collected from high-risk aborted women (ages 15-45 years) who attended Al-Medina Private Laboratory from February to December 2022.Sera were tested for heterophile antibodies(HA) associated with Infectious Mononucleosis (IM) caused by EBV by Latex Agglutination slide test (IM Quick test) and were tested for IgM and IgG antibodies against EBV-CA in serum using the ELISA kit. Sera from the patients and healthy controls were analyzed for Glutamate-Pyruvate Transaminase (GPT), Glutamic Oxaloacetic Transaminase (GOT), Lactate Dehydrogenase (LDH), and Alkaline phosphatase. Compared to healthy controls, the data showed that the late phase with loss and reactivated infection was responsible for 25% of cases and that the acute and late infection cases had a high of 64%. There were significant differences in the level of these hormones;aborted women showed increased levels of serum ALP (70.83) while having a reverse effect with serum ALT (11.7) and AST (25.43). EBV activation was higher in the aborted women. The study would help to determine the role of EBV in the pathogenesis of abortion. [ABSTRACT FROM AUTHOR]

Inspired by the split decomposition of graphs and rank-width, we introduce the notion of r-splits. We focus on the family of r-splits of a graph of order n, and we prove that it forms a hypergraph with several properties. We prove that such hypergraphs can be represented using only O(nr+1) of its hyperedges, despite its potentially exponential number of hyperedges. We also prove that there exist hypergraphs that need at least (nr) hyperedges to be represented, using a generalization of set orthogonality. [ABSTRACT FROM AUTHOR]

Dense subgraphs convey important information and insights about a graph structure. Several applications, such as graph visualization, graph summarization, and complex network analysis rely on discovering the dense subgraphs available within the target graph. This enumeration problem has been intensively addressed by several research communities but remains a challenging problem because of its importance and use. This problem generalizes the clique problem and is thus NP-hard and not approximable in polynomial time in general graphs. In this paper, we propose to deal with this problem in a specific application case where the type of the discovered dense subgraphs is important. This is the case of graph summarization for example. However, existing dense subgraph discovery algorithms are either dedicated to specific kind of structures such as cliques and bicliques or are too general and list the dense subgraphs without giving their types. To deal with this issue, we provide a unified approach that lists dense subgraphs and provides their types. Our approach relies on deep learning. More precisely, we enrich exiting structural node embedding with extra information, computed on node neighborhoods, to effectively capture their belonging to dense subgraphs. We evaluate our approach on several datasets to attest its efficiency and its effectiveness on two main applications: graph summarization and graph clustering. Our results show that our method significantly improves the compression rate in graph summarization, achieving up to 30% size reduction for the largest graphs tested and exceeding 80% for sparse graphs. Additionally, even for highly dense graphs, our method consistently achieves a non-zero AMI score, outperforming other approaches on the clustering application. • We propose a deep learning approach to dense subgraph mining. • We aim to simply give insights about a graph structure. • We compute a node parameter that reveals how much dense the graph is around it. • We apply this approach successfully in graph summarization and clustering. [ABSTRACT FROM AUTHOR]

They have conducted to test the efficiency of fat pomegranate extract supported by Silver nanoparticle (AgNp) to inhibit the growth of Staphylococcus aureus in the study, isolated from teeth decay from March to July 2020. Thirty isolates were purified and identified according to morphological, biochemical, Physiological tests and confirmed by the API32 ID Staph system. All the bacterial was isolates indicated that Impanel is highly effective against Staph. aureus and all were resistant to Furazolidone and their ability to produce the Biofilms at a rate of (100%). Still, the use of pomegranate fat extract showed a different inhibition, the highest at a concentration of (800 mg/ml) with an inhibition zone of (18) mm, but the lowest level of (100, mg / ml) with the inhibitory zone (9)mm. AgNp alone at a concentration of (1%, 2% 3% and 4%) led to highest bacterial inhibition at a concentration of (4%) with a diameter zone of inhibition (12-18) mm The effectiveness of the extract of pomegranate-fortified with AgNp increasing the inhibition of bacterial growth with different concentrations, the highest rate of inhibition at (40%) and the average inhibition diameter was (25) mm. [ABSTRACT FROM AUTHOR]

A filamentous cyanobacterium, Trichormus sp. IMU26, capable of rapid growth and high phycobiliprotein (PBP) production under N2-fixing conditions was isolated. The strain has been maintained in N-free BG-11 medium for more than 20 months upon isolation. Nitrogen supply resulted in higher soluble protein and saccharide content but a lower growth rate and PBP production in Trichormus sp. IMU26. Short-term N-P deprivation induced PBP production with no clear change in growth while growth and PBP content decreased in the longer incubation period. Induction of PBP production in N-P-deprived cells was characterized by FTIR analysis and change in carotenoid-pigment interactions. Rapid induction of zeaxanthin and β-carotene production and slight reduction of echinenone and canthaxanthin levels might be associated with increased PBP levels in short-term N-P deprivation of Trichormus sp. IMU26. Overall, long-term diazotrophic growth of N2-fixing cyanobacteria may increase the PBP yield. [ABSTRACT FROM AUTHOR]

We present a silent self-stabilizing distributed algorithm computing a maximal |$\ p$| -star decomposition of the underlying communication network. Under the unfair distributed scheduler, the most general scheduler model, the algorithm converges in at most |$12\Delta m + \mathcal{O}(m+n)$| moves, where |$m$| is the number of edges, |$n$| is the number of nodes and |$\Delta $| is the maximum node degree. Regarding the time complexity, we obtain the following results: our algorithm outperforms the previously known best algorithm by a factor of |$\Delta $| with respect to the move complexity. While the round complexity for the previous algorithm was unknown, we show a |$5\big \lfloor \frac{n}{p+1} \big \rfloor +5$| bound for our algorithm. [ABSTRACT FROM AUTHOR]

In this paper, a novel robust adaptive fuzzy control is presented for a quite general class of multivariable nonlinear systems with actuators' nonlinearities (saturation with dead zone) and uncertain dynamics. The backstepping concept in combination with the variable-structure control framework and Lyapunov approach is used to design this adaptive fuzzy control. The fuzzy systems are incorporated in the controller for approximating online the unknown system dynamics. In the controller design and stability analysis, the control gain matrices, which are not necessarily symmetric and definite, are decomposed via the so-called SDU matrix decomposition lemma into a product of three main useful matrices, namely a symmetric definite-positive matrix, a diagonal constant matrix with + 1 or − 1 in its main diagonal and a unity upper triangular matrix. It is shown that the proposed adaptive fuzzy control is able to ensure the uniform ultimate boundedness of all solutions of the closed-loop system, as well as the convergence of the underlying tracking errors. Finally, in a numerical simulation framework, the effectiveness of the presented controller is illustrated on two practical examples. [ABSTRACT FROM AUTHOR]

Self-monitoring is a simple and effective mechanism for surveilling wireless sensor networks, especially to cope against faulty or compromised nodes. A node v can monitor the communication over a link e if both end-nodes of e are neighbors of v . Finding a set of monitoring nodes satisfying all monitoring constraints is called the edge-monitoring problem . The minimum edge-monitoring problem is known to be NP-complete. In this paper, we present a novel self-stabilizing algorithm for computing a minimal edge-monitoring set under the unfair distributed scheduler. For sparse networks the time complexity of this new algorithm is much lower than the currently best known algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we introduce and study a new coloring problem of a graph called the dominated coloring. A dominated coloring of a graph $$G$$ is a proper vertex coloring of $$G$$ such that each color class is dominated by at least one vertex of $$G$$ . The minimum number of colors among all dominated colorings is called the dominated chromatic number, denoted by $$\chi _{dom}(G)$$ . In this paper, we establish the close relationship between the dominated chromatic number $$\chi _{dom}(G)$$ and the total domination number $$\gamma _t(G)$$ ; and the equivalence for triangle-free graphs. We study the complexity of the problem by proving its NP-completeness for arbitrary graphs having $$\chi _{dom}(G) \ge 4$$ and by giving a polynomial time algorithm for recognizing graphs having $$\chi _{dom}(G) \le 3$$ . We also give some bounds for planar and star-free graphs and exact values for split graphs. [ABSTRACT FROM AUTHOR]

Graph Embedding, a learning paradigm that represents graph vertices, edges, and other semantic information about a graph into low-dimensional vectors, has found wide applications in different machine learning tasks. In the past few years, we have had a plethora of methods centered on graph embedding using different techniques, such as spectral classification, matrix factorization and learning. In this context, choosing the appropriate dimension of the obtained embedding remains a fundamental issue. In this paper, we propose a compact representation of a node's neighborhood, including attributes and structure, that can be used as an additional dimension to enrich node embedding, to ensure accuracy. This compact representation ensures that both semantic and structural properties of a node's neighboring-hood are properly captured in a single dimension. Consequently, we improve the learned embedding from state-of-the-art models by introducing the neighborhood compact representation for each node as an additional layer of dimensionality. We leverage on this neighborhood encoding technique and compare with embedding from state-of-the-art models on two learning tasks: node classification and link prediction. The performance evaluation shows that our approach gives a better prediction and classification accuracy in both tasks. [ABSTRACT FROM AUTHOR]

Abstract: We consider the problem of matching unrooted unordered labeled trees, which refers to the task of evaluating the distance between trees. One of the most famous formalizations of this problem is the computation of the edit distance defined as the minimum-cost sequence of edit operations that transform one tree into another. Unfortunately, this problem has been proved to be NP-complete. In this paper, we propose a new algorithm to measure distance between unrooted unordered labeled trees. This algorithm uses a specific graph coloring to decompose the trees into small components (stars and bistars). Then, it determines a distance between two trees by computing the edit distance between their components. We prove that the proposed distance is a pseudo-metric and we analyze its time complexity. Our experimental evaluations on large synthetic and real world datasets confirm our analytical results and suggest that the distance we propose is accurate and its algorithm is scalable. [Copyright &y& Elsevier]

In this paper, we study the complexity of the edge monitoring problem. A vertex v monitors an edge e if both endpoints together with v form a triangle in the graph. Given a graph G = (V , E) and a weight function on edges c where c (e) is the number of monitors that needs the edge e , the problem is to seek a minimum subset of monitors S such that every edge e in the graph is monitored by at least c (e) vertices in S. Therefore, we study the edge monitoring problem on several graph classes such as complete graphs, block graphs, cographs, split graphs, interval graphs and planar graphs. We also generalize the problem by adding weights on vertices. [ABSTRACT FROM AUTHOR]

Background: The restoration of intestinal continuity after open abdominal surgery can be technically challenging. The authors describe their experience with the laparoscopic approach to attempted reversal for patients with an exteriorized intestine. Methods: A consecutive series of patients under the care of a single surgeon (D.B.) underwent laparoscopic restoration of intestinal continuity (LapRICon). All the patients first underwent exclusion of intraabdominal sepsis with computed tomography (CT) scanning and then preoperative localization of proximal and distal bowel ends via water-soluble contrast studies. Stomal sites were used for initial access, establishment of capnoperitoneum, and formation of anastomoses extracorporeally. All adhesiolysis and mobilization of bowel ends were performed intracorporeally. Pre-, intra-, and postoperative data were collected for all the patients. Return of intestinal function, overall hospital length of stay, and postoperative complications were collected. Nonparametric statistics were used to analyze the data. Results: A total of 13 patients (6 women) were followed up for 9 months (interquartile range [IQR], 5-16 months). The median age of the patients was 39 years (IQR, 28-64 years). Nine patients were categorized as American Society of Anesthesiology (ASA) class 1. One patient was ASA 2, and the remaining patients were ASA 3. The median colorectal physiologic and operative severity scores for the enumeration of mortality and morbidity (CR-POSSUM) were 0.68 (IQR, 0.68-1.72). The intraoperative blood loss was minimal (median 30 ml; IQR, 20-125 ml). The median operative duration was 240 min (IQR, 180-240 min), and a median of 4 ports (IQR, 3-5 ports) were used. Enterocolonic anastomoses were fashioned in six patients, enterorectal anastomoses in two patients, and enteroentero anastomoses in three patients. A single patient had multiple anastomoses. The median time to return of intestinal function was 5 days (IQR, 3-13 days), and the overall hospital stay was 8 days (IQR, 5-24 days). Four complications (25%) (2 recurrent fistulas, 1 anastomotic leak, and 1 open conversion) occurred in this series of patients. Conclusions: The LapRICon procedure is a feasible technique with acceptable morbidity. Several principles and techniques are described to aid the surgeon who wishes to embark on use of such a technique. [ABSTRACT FROM AUTHOR]

Introduction: Computed tomography angiography (CTA) is the gold standard follow-up modality after endovascular aneurysm repair (EVAR). A potential alternative noninvasive and less expensive modality is duplex ultrasound scanning (DUS). Methods: We studied 314 follow-up paired scans (DUS and CTA) in 59 patients with EVAR. Results: Endoleak--Endoleak was detected in 23.7% patients. The sensitivity and specificity rates of DUS were 54% and 95.3%, respectively. All 9 endoleaks that needed secondary intervention were detected on DUS. Eight of those were identified within a year after EVAR. Sac size--The mean difference in maximum diameter between the DUS and CTA was ≤5 mm in 84.5% of cases and ≤10 mm in 97.1%. Graft patency-There was 100% agreement between CTA and DUS. Conclusions: Duplex ultrasound scanning was reliable as it detected all the leaks that needed reintervention after EVAR. Duplex ultrasound scanning showed similar results to CTA in detecting sac size and patency. [ABSTRACT FROM AUTHOR]

There are concerns about the safety of the dextropropoxyphene and acetaminophen fixed-dose combination, particularly in patients with psychiatric morbidity, which has led to a phased withdrawal of this fixed-dose combination in many countries. A retrospective prescription audit was conducted to evaluate the dextropropoxyphene + acetaminophen fixed-dose combination prescribing pattern in the major psychiatric hospital of Bahrain. The data analysis was performed using SPSS/PC+ version 14.0. Prescriptions with the dextropropoxyphene + acetaminophen fixed-dose combination comprised 11.8% of all dispensed prescriptions and in most instances for outpatients undergoing substance abuse rehabilitation. Nearly half of the patients received ≥20 tablets of this fixed-dose combination (mean ± SD: 30.9 ± 13.1; range 20–126) as multiple doses. The dextropropoxyphene + acetaminophen fixed-dose combination was often co-prescribed with psychotropics, such as benzodiazepines (BZDs) (25.4%), BZDs + antidepressants (62.9%), BZDs + antipsychotics (3.7%) and BZDs + anticonvulsants (1.9%). Approximately 40% of prescriptions with the dextropropoxyphene + acetaminophen fixed-dose combination were written ‘as required’ ( prn), basis. Despite poor safety and efforts to restrict or withdraw worldwide, the dextropropoxyphene + acetaminophen fixed-dose combination continues to be irrationally prescribed to outpatients undergoing substance abuse rehabilitation in Bahrain. Health policy decision-makers should introduce a phased withdrawal of this drug from clinical use. In the meanwhile, it is important to create awareness among prescribers of the risks associated with over-dosage of the dextropropoxyphene + acetaminophen fixed-dose combination and its interaction with other psychotropic medications. [ABSTRACT FROM AUTHOR]

Let k be a positive integer, Sk and Ck denote, respectively, a star and a cycle of k edges. Kn is the usual notation for the complete multigraph on n vertices and in which every edge is taken times. In this paper, we investigate necessary and sufficient conditions for the existence of the decomposition of Kn into edges disjoint of stars Sk's and cycles Cu's. [ABSTRACT FROM AUTHOR]

Objective. To study the total amount of sedative drugs administered to patients in the intensive care unit (ICU) before and after tracheostomy. Design. Prospective observational study. Setting. Twelve-bedded general ICU that was expanded to an 18-bedded general ICU. Subjects. Twenty-two patients who had a tracheostomy inserted during their ICU stay. Interventions. None. End points. The total amount of sedative drugs administered to patients three days before and three days after insertion of tracheostomy. Measurements and main results. During the study period 447 patients were admitted to ICU, 27 (5.6%) had a tracheostomy. Four patients were excluded from the study because of the presence of hypoxic brain damage or a permanent tracheostomy prior to ICU admission. Twenty-three patients were studied. The median age was 65, median initial 24  h APACHE II score was 22, median length of stay was 36 days, and median time of performing the tracheostomy was 14 days. Twelve (52%) patients died and one patient was transferred to another centre the day after tracheostomy and was therefore not included in the comparison of sedation use before and after tracheostomy. Alfentanil, morphine, propofol and midazolam were used in 17 (77.3%), 8 (36.4%), 19 (86.4%) and 9 (40.9%) patients respectively. Overall, there was a significant reduction in the total amount of alfentanil ( p =0.01) and propofol ( p =0.01) administered before and after tracheostomy. One patient (4.5%) did not receive sedation before or after tracheostomy. Sedative drug use was reduced after tracheostomy in 13 (59%) patients and slightly increased in one (4.5%) patient. Sedative drugs were altered in 7 (31.8%) patients. Ten patients received only propofol and/or alfentanil for sedation. For these patients, there was a significant reduction in the use of both these agents after tracheostomy, p =0.02 and p [ABSTRACT FROM AUTHOR]

Presents an evaluative study of the outcome of problem-based curriculum programme at the College of Medicine and Medical Sciences of the Arabian Gulf University (CMMS-AGU) in Bahrain in relation to the institutional goals. Evaluation programme's two aspects of curriculum implementation; How an evaluative study was done; Results of the evaluation.

A vertex subset S of a graph G = (V , E) is a [ 1 , 2 ] -dominating set if each vertex of V ∖ S is adjacent to either one or two vertices in S. The minimum cardinality of a [ 1 , 2 ] -dominating set of G , denoted by γ [ 1 , 2 ] (G) , is called the [ 1 , 2 ] -domination number of G. In this paper, the [ 1 , 2 ] -domination and the [ 1 , 2 ] -total domination numbers of the generalized Petersen graphs P (n , 2) are determined. [ABSTRACT FROM AUTHOR]

In this paper, we are interested in four proper vertex colorings of graphs, with additional domination property. In the dominator colorings , strong colorings and strict strong colorings of a graph G , every vertex has to dominate at least one color class. Conversely, in the dominated colorings of G , every color class has to be dominated by at least one vertex. We study arbitrary graphs as well as P 4 -sparse graphs, P 5 -free graphs, bounded treewidth graphs and claw-free graphs. [ABSTRACT FROM AUTHOR]

The triangle partition problem is a generalization of the well-known graph matching problem consisting of finding the maximum number of independent edges in a given graph, i.e., edges with no common node. Triangle partition instead aims to find the maximum number of disjoint triangles. The triangle partition problem is known to be NP-complete. Thus, in this paper, the focus is on the local maximization variant, called maximal triangle partition (MTP). Thus, paper presents a new self-stabilizing algorithm for MTP that converges in O( m) moves under the unfair distributed daemon. [ABSTRACT FROM AUTHOR]

Drug design is a research process with a goal of creating a chemical drug to produce the desired biological effect. Because of the long time and the high cost issues associated with traditional drug discovery, there is a need to develop new techniques and strategies to increase the diminishing effectiveness of traditional approaches. Ligand-Based Virtual Screening (LBVS) plays a vital role in the early stage of the drug discovery. It could constitute a possible solution to solve the time and cost problems. Subsequently, the researchers are looking for new methods to find new active compounds and bring them to market in a short time. LBVS can be enhanced by different methods and strategies such as Machine Learning and Deep Learning. In this paper, a Deep Convolutional Neural Network method is proposed to enhance the performances of Ligand-Based Virtual Screening process (DCNNLB). Two main contributions are presented in this paper, The first contribution consists of designing a model based on Deep Convolutional Neural Network (DCNN) for LBVS. We propose several topological network models to find the one that gives the best performance such as accuracy and recall. For this, many network topology configurations have been proposed, and a variety of parameters have been taken into account. Furthermore, our proposed model is trained on all compounds of all activity classes of the Drug Data Report Database (MDDR). Thus, it presented a mean accuracy of 0.98 for all three MDDR Datasets. The second contribution is to generate a new learning representation in order to better represent chemical compound. This representation is based on the extraction of the automatic features learning from the weights of our proposed model. Consequently, it is very efficient in calculating molecular similarity and performances of the LBVS process. The obtained results with the three different datasets drawn from the MDDR and the performance evaluation with ANOVA test, have proved the superiority in performance of our proposed method compared to the different conventional methods. [Display omitted] • New molecular representations obtained by the proposed deep convolutional model. • Enhancement in effectiveness of similarity searching with DCNNLB method in LBVS. • Decreasing in training time by using the molecular learning representation. • The proposed DCNNLB method significantly outperforms the conventional TAN method. [ABSTRACT FROM AUTHOR]

In computer networks area, the minimal dominating sets (MDS) and maximal independent sets (MIS) structures are very useful for creating virtual network overlays. Often, these set structures are used for designing efficient protocols in wireless sensor and ad-hoc networks. In this paper, we give a particular interest to one kind of these sets, called Independent Strong Dominating Set (ISD-set). In addition to its domination and independence properties, the ISD-set considers also node's degrees that make it very useful in practical applications where nodes with larger degrees play important role in the networks. For example, some network clustering protocols chose nodes with large degrees to be cluster-heads, which is exactly the result obtained by an ISD-set algorithm. Thence, we propose the first distributed self-stabilizing algorithm for computing an ISD-set of an arbitrary graph (called ISDS). Then, we prove that ISDS algorithm operates under the unfair distributed scheduler and converges after at most rounds requiring only space memory per node where Δ is the maximum node degree. The complexity of ISDS algorithm in rounds has the same order as the best known self-stabilizing algorithms for finding MDS and MIS. Moreover, performed simulations and comparisons with well-known self-stabilizing algorithms for MDS and MIS problems showed the efficiency of ISDS, especially for reducing the cardinality of dominating sets founded by the algorithms. [ABSTRACT FROM AUTHOR]

A letter to the editor about whipple procedure for chronic pancreatitis in a Jehovah's Witness is presented.